Abstract
Individuals, organizations, and connected objects produce and publish vast data on the web. These data are then combined into mashups to produce new valuable data. However, combining data from different sources may lead to data uncertainty because these sources contain heterogeneous, contradictory, or incomplete information. In expert and intelligent systems, the word “uncertainty” is related to working with inaccurate data, imprecise and incomplete information, and unreliability of results that can lead to irrational decisions. An expert and intelligent system can consider all the uncertain information, and manage web services and web resources based on the best possible answer rather than on the quality of the exact answer to manage such problems. This paper proposes a new model to define, compute, and interpret uncertain web resources in the context of classical hypertext navigation and evaluation of data queries. The experimental study as well as the analysis of the results, which we carried out on different corpora, confirmed the usefulness of our approach. It provides the effect of the treatment of uncertainty on the execution time and the importance of calculating the confidence level of the response returned to the user. The analysis of the IT execution time shows that the time required for the composition of the services by our approach is negligible, as compared to that of the other approach studied. The impact of the variation in the number of nodes of type “mux” and type “ind” were also evaluated. Our algorithm checks all possibilities in polynomial time and can adapt to many possibilities of multiplexing values.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Maleshkova, M., Pedrinaci, C., Domingue, J.: Investigating web APIs on the world wide web. In: 8th IEEE European Conference on Web Services (ECOWS 2010), 1–3 December 2010, Ayia Napa, Cyprus (2010). DBLP:conf/ecows/2010
Benslimane, D., Dustdar, S., Sheth, A.P.: services mashups: the new generation of web applications. IEEE Internet Comput. 12, 13–15 (2008)
Halevy, A.Y., Rajaraman, A., Ordille, J.J.: Data integration: the teenage years. In: Proceedings of the 32nd International Conference on Very Large Data Bases, Seoul, Korea (2006)
Kharlamov, E., Nutt, W., Senellart, P.: Updating probabilistic XML. In: Proceedings of the 2010 EDBT/ICDT Workshops, Lausanne, Switzerland (2010)
Nierman, A., Jagadish, H.V.: ProTDB: probabilistic data in XML. In: VLDB 2002, Proceedings of 28th International Conference on Very Large Data Bases (2002)
Benslimane, D., Sheng, Q.Z., Barhamgi, M., Prade, H.: The uncertain web: concepts, challenges, and current solutions. TOIT 16, 1–6 (2016)
Lemos, A.L., Daniel, F., Benatallah, B.: Web service composition: a survey of techniques and tools. ACM Comput. Surv. (CSUR) 48, 1–41 (2016)
Malki, A., et al.: Data services with uncertain and correlated semantics. WWWJ 19, 157–175 (2016)
Yu, Q., Liu, X., Bouguettaya, A., Medjahed, B.: Deploying and managing Web services: issues, solutions, and directions. VLDBJ 17, 537–572 (2008)
Agrawal, P., Sarma, A.D., Ullman, J., Widom, J.: Fondements de l’intgration des donnes incertaines. Proc. VLDB Endow. 3, 1080–1090 (2010)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Omri, A., Benslimane, D., Omri, M.N. (2023). Efficient Model for Probabilistic Web Resources Under Uncertainty. In: Quaresma, P., Camacho, D., Yin, H., Gonçalves, T., Julian, V., Tallón-Ballesteros, A.J. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2023. IDEAL 2023. Lecture Notes in Computer Science, vol 14404. Springer, Cham. https://doi.org/10.1007/978-3-031-48232-8_41
Download citation
DOI: https://doi.org/10.1007/978-3-031-48232-8_41
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-48231-1
Online ISBN: 978-3-031-48232-8
eBook Packages: Computer ScienceComputer Science (R0)